布里斯托大学PhD position in Constructing an epidemiological modelling framework to maintain health security against resurgent infectious diseases申请条件要求-申请方
主办方
布里斯托大学
PhD直招介绍
About the Project
A major hazard to public health is the resurgence of infectious diseases that were once believed to be eliminated from a population [1]. Recent examples include regional resurgences of Polio after an exhaustive vaccination campaign [2], the rise of syphilis after decades of antibiotics had largely made it a disease of the past [3], and an uptick of tuberculosis following the onset of war [4]. While each case tells its own unique story, they each raise the same important question: at what point can we declare that a disease is eliminated, and how do we ensure long-term security after this has been achieved?
Mathematical modelling is useful to contextualise various stages of an epidemic. While pathogen emergence, exponential epidemic growth, endemicity, and the effects of interventions have all been modelled extensively [5], the post-elimination risk of disease resurgence has not. There is no established framework we can apply to assess the risk of disease reemergence in an environment once hostile to the pathogen.
The World Health Organisation has ambitious targets for disease elimination, for example viral Hepatitis by 2030 [6], but less has been said about how disease security is maintained in the following years.
Aims & Objectives
This project aims to advance the field of mathematical epidemiology in the area of infectious disease resurgence, and provide insights to help maintain health security following the elimination of an infectious disease.
Objectives:
(O1) Formulate a robust definition of disease elimination based on the risk of resurgence
(O2) Build a taxonomy of resurgent diseases and reasons behind cases of resurgence
(O3) Define mathematically the conditions that lead to resurgence following a successful elimination campaign
(O4) Develop modelling tools to inform policy decisions regarding resurgence
(O5) Study cases of potential resurgence in real-world settings such as viral hepatitis after 2030
Methods
Methods are categorised as follows:
Literature review: For O1 and O2, the candidate will develop skills in performing narrative and, possibly, systematic literature reviews. They will obtain deep knowledge of epidemiology and public health responses to infectious disease threats.
Mathematical modelling: For O3 (and potentially O4) the candidate will become proficient in formulating a mathematical model, then applying analytical and numerical techniques to extract insights about the system. They will develop expertise in random variables and a deep understanding of rare extreme events.
Computational modelling: For O4, simulation models will be coded in python, R, or Matlab. They will develop bespoke models for specific disease systems from existing resources, e.g. the Gillespe algorithm for stochastic processes, agent-based modelling for encoding complex behavioural characteristics.
Incorporating data: For O5, the candidate will apply data handling, visualisation, and statistical analysis to epidemiological and behavioural data. Advanced methods (e.g. Bayesian) will be applied to calibrate models to particular disease settings. Where necessary, high performance computing facilities will be utilised.
Communication: The candidate will develop skills in communicating scientific results to relevant stakeholders. This may include engagement with policy, the public, and other academics.
Training Plan
The candidate will initially be assessed to identify areas of interest and skills to be developed. They will be integrated into our wider research group and immediately benefit from the support of a diverse group of researchers with expertise in quantitative methodologies, evidence synthesis, epidemiology and modelling. They will join a peer group of 11 other PhD students within our team who meet biweekly. In addition to relevant courses within the university, they will be encouraged to attend summer schools, conferences, and participate in a work placement within UKHSA which we will help to arrange.
Deadline: 16:00 GMT Friday 13th December 2024
Supervisors: Dr Jack Stone, Dr Ewan Colman & Dr Zoe Ward
Key words: Infectious disease, mathematical modelling, health security, reemergence, resurgence, viral hepatitis
布里斯托大学 PhD position in Constructing an epidemiological modelling framework to maintain health security against resurgent infectious diseases项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
The University of Bristol Scholarship is funded for four years. It includes an annual stipend at the UKRI rate (£19,237 in 2024/25), tuition fees and research costs (£2000 per year).
布里斯托大学Phd申请条件和要求都有哪些？PhD position in Constructing an epidemiological modelling framework to maintain health security against resurgent infectious diseases项目是不是全奖？有没有奖学金？下面我们一起看一下布里斯托大学申请Phd直招需要具备哪些条件和要求，以及托福、雅思语言成绩要到多少才能申请。
申请要求
Before applying, please check the entry requirements( https://www.findaphd.com/common/clickCount.aspx?theid=176844&type=184&DID=4465&url=https%3a%2f%2fwww.bristol.ac.uk%2fstudy%2fpostgraduate%2fresearch%2ftranslational-health-sciences%2f%23%3a%7e%3atext%3dREF%25202021%2520results-%2cEntry%2520requirements%2c-An%2520upper%2520second ) for the programme.
报名方式
申请链接
联系人
邮箱：fohs-pgadmissions@bristol.ac.uk
招生人信息
Dr Jack Stone
邮箱：j.stone@bristol.ac.uk
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